Molecular characterisation and tracking of severe acute respiratory syndrome coronavirus 2 in Thailand, 2020–2022

Puenpa, Jiratchaya; Rattanakomol, Patthaya; Saengdao, Nutsada; Chansaenroj, Jira; Yorsaeng, Ritthideach; Suwannakarn, Kamol; Thanasitthichai, Somchai; Vongpunsawad, Sompong; Poovorawan, Yong

doi:10.1007/s00705-022-05666-6

Cited by 31 publications

(36 citation statements)

References 29 publications

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“…The vertical dotted lines indicate the quarter, and the number above the bar graph indicates infection-induced seropositivity estimated for each quarter. Color shaded areas indicate the number of nasopharyngeal swab samples that tested positive (right Y axis) and subsequently identified the SARS-CoV-2 variants (n = 7,729) that was obtained from our previous study [ 7 ]. Data on SARS-CoV-2 variants were identified using sequencing and multiplex real-time reverse transcription polymerase chain reaction (RT-PCR) to depict the predominant wave for individual SARS-CoV-2 variants in Thailand.…”

Section: Resultsmentioning

confidence: 99%

“…The omicron variant was first detected in Thailand in mid-December 2021. The incidence of omicron infection rapidly increased and subsequently became the predominant variant by January 2022 [ 7 ]. A study demonstrated that the omicron variant was highly transmissible and can evade the immune system even in vaccinated or previously infected individuals [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

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SARS-CoV-2 infection- induced seroprevalence among children and associated risk factors during the pre- and omicron-dominant wave, from January 2021 through December 2022, Thailand: A longitudinal study

et al. 2023

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Background Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection can be asymptomatic in young children. Therefore, the true rate of infection is likely underestimated. Few data are available on the rate of infections in young children, and studies on SARS-CoV-2 seroprevalence among children during the omicron wave are limited. We assessed the SARS-CoV-2 infection-induced seroprevalence among children and estimated the associated risk factors for seropositivity. Methods A longitudinal serological survey was conducted from January 2021 through December 2022. The inclusion criteria were healthy children between 5 and 7 years old and their parents or legal guardians provided written informed consent. Samples were tested for anti-nucleocapsid (N) IgG and anti-receptor binding domain (RBD) IgG using a chemiluminescent microparticle immunoassay (CMIA), and total anti-RBD immunoglobulin (Ig) was detected using an electrochemiluminescence immunoassay (ECLIA). The vaccination and SARS-CoV-2 infection history were collected. Results In all, 457 serum samples were obtained from 241 annually followed-up children in this longitudinal serological survey. Of these, 201 participants provided samples at two serial time points—during the pre-omicron and omicron-dominant wave. Overall, seroprevalence induced by SARS-CoV-2 infection increased from 9.1% (22/241) during the pre-omicron to 48.8% (98/201) during the omicron wave. Amongst seropositive individuals, the infection-induced seropositivity was lower in vaccinated participants with two doses of BNT162b2 than in the unvaccinated participants (26.4% vs. 56%; OR, 0.28; 95%CI: 0.14–0.58). Nevertheless, the ratio of seropositive cases per recalled infection was 1.63 during the omicron dominant wave. The overall seroprevalence induced by infection, vaccination, and hybrid immunity was 77.1% (155/201) between January and December 2022. Conclusions We report an increase in infection-induced seroprevalence among children during the omicron wave. These findings highlight that a seroprevalence survey can help determine the true rate of infection, particularly in asymptomatic infection, and optimize public health policies and vaccine strategies in the pediatric population.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 infection- induced seroprevalence among children and associated risk factors during the pre- and omicron-dominant wave, from January 2021 through December 2022, Thailand: A longitudinal study

et al. 2023

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“…The outbreaks were most intense in the Bangkok Metropolitan Region (BMR) – an inter-connected and densely populated area of the country, comprising the capital city of Thailand, Bangkok, and five surrounding provinces, Nakhon Pathom, Nonthaburi, Pathum Thani, Samut Prakan and Samut Sakhon. While molecular evolution of SARS-CoV-2 circulating in Thailand in 2020–2022 has already been previously described [3, 4], a comprehensive spatiotemporal analysis of the virus is still lacking.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal evolution of SARS-CoV-2 in the Bangkok metropolitan region, Thailand, 2020–2022: implications for future outbreak preparedness

Aiewsakun,

Jamsai,

Phumiphanjarphak

et al. 2023

Microbial Genomics

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Thailand experienced five waves of coronavirus disease 2019 (COVID-19) between 2020 and 2022, with the Bangkok Metropolitan Region (BMR) being at the centre of all outbreaks. The molecular evolution of the causative agent of the disease, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has previously been characterized in Thailand, but a detailed spatiotemporal analysis is still lacking. In this study, we comprehensively reviewed the development and timelines of the five COVID-19 outbreaks in Thailand and the public health responses, and also conducted a phylogenetic analysis of 27 913 SARS-CoV-2 genomes from Thailand, together with 7330 global references, to investigate the virus’s spatiotemporal evolution during 2020 and 2022, with a particular focus on the BMR. Limited cross-border transmission was observed during the first four waves in 2020 and 2021, but was common in 2022, aligning well with the timeline of change in the international travel restrictions. Within the country, viruses were mostly restricted to the BMR during the first two waves in 2020, but subsequent waves in 2021 and 2022 saw extensive nationwide transmission of the virus, consistent with the timeline of relaxation of disease control measures employed within the country. Our results also suggest frequent epidemiological connections between Thailand and neighbouring countries during 2020 and 2021 despite relatively stringent international travel controls. The overall sequencing rate of the viruses circulating in the BMR was ~0.525 %, meeting the recommended benchmark, and our analysis supports that this is sufficient for tracking of the trend of the virus burden and genetic diversity. Our findings reveal insights into the local transmission dynamics of SARS-CoV-2 in Thailand, and provide a valuable reference for planning responses to future outbreaks.

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“…Time course of the first infection (circle) and reinfection (square) were plotted versus the sequencing data of the SARS-CoV-2 predominant variant obtained in our previous study [5]. …”

Section: Resultsmentioning

confidence: 99%

“…The timing of the infection was used to assign the pre-Omicron or Omicron infection period. According to the sequenced surveillance data for the predominant SARS-CoV-2 variant obtained in our previous study in Thailand [5], infections that occurred before January 2022 were considered from the pre-Omicron infection period.…”

Section: Methodsmentioning

confidence: 99%

SARS-CoV-2 reinfection with Omicron BA.2.75 subvariants in Thai Adults in Thailand

Assawakosri,

Sudhinaraset,

Chansaenroj

et al. 2023

Preprint

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Omicron subvariants of SARS-CoV-2 may resist vaccine- or infection-induced immunity thereby increasing the risk of reinfections in previously infected persons. This study aimed to investigate the clinical severity and the average time to the onset of Omicron reinfection. This survey study collected clinical data on Omicron reinfection. Information on time of infection, reinfection interval, overall clinical presentation, and severity of infection was reported. The total prevalence of symptoms among 201 participants was significantly higher in the first infection (risk difference (RD), 9.86%; 95% CI, 7.54–12.19]) compared to the second infection, and the hospitalization rate among all participants was significantly lower for the second infection than the primary infection (odds ratio (OR), 6.25; 95% CI, 2.158−24.71). The prevalence of symptoms compared with the first infection with pre-Omicron variants was similar to that of the first infection with the Omicron variant (RD, 2.56%; 95% CI, -6.14–1.01). However, the hospitalization rate for pre-Omicron primary infection was significantly higher (OR, 6.76; 95% CI, 2.87–15.87]) than that observed with Omicron variants. The severity of the primary infection and of a pre-Omicron variant was greater than that of a secondary infection or with an Omicron variant.

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Molecular characterisation and tracking of severe acute respiratory syndrome coronavirus 2 in Thailand, 2020–2022

Cited by 31 publications

References 29 publications

SARS-CoV-2 infection- induced seroprevalence among children and associated risk factors during the pre- and omicron-dominant wave, from January 2021 through December 2022, Thailand: A longitudinal study

SARS-CoV-2 infection- induced seroprevalence among children and associated risk factors during the pre- and omicron-dominant wave, from January 2021 through December 2022, Thailand: A longitudinal study

Spatiotemporal evolution of SARS-CoV-2 in the Bangkok metropolitan region, Thailand, 2020–2022: implications for future outbreak preparedness

SARS-CoV-2 reinfection with Omicron BA.2.75 subvariants in Thai Adults in Thailand

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